Copper Catalysts for Selective CC Bond Cleavage of β‐O‐4 Lignin Model Compounds
Bibliographic record
Abstract
Abstract The reactivity of homogeneous copper catalysts towards the selective CC bond cleavage of both phenolic and non‐phenolic arylglycerol β‐aryl ether lignin model compounds has been explored. Several copper precursors, nitrogen ligands, and solvents were evaluated in order to optimize the catalyst system. Using the optimized catalyst system, copper(I) trifluoromethanesulfonate [Cu(OTf)]/L/TEMPO (L=2,6‐lutidine, TEMPO=2,2,6,6‐tetramethyl‐piperidin‐1‐yl‐oxyl), aerobic oxidation of the non‐phenolic β‐O‐4 lignin model compound proceeded with good selectivity for CαCβ bond cleavage, affording 3,5‐dimethoxybenzaldehyde as the major product. Aerobic oxidation of the corresponding phenolic β‐O‐4 lignin model proceeded with different selectivity, affording 2,6‐dimethoxybenzoquinone and α,β‐unsaturated aldehyde products resulting from cleavage of the CαCaryl bond. At low catalyst concentrations, however, a change in selectivity was observed as oxidation of the benzylic secondary alcohol predominated with both substrates. magnified image
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".